Disclaimer:

These are my personal views and are meant for Informational purpose only. Please verify the Information via Professional help or via Official references before acting upon the information provided in this Blog.

I like frameworks — it helps structure your thoughts. One of the most basic questions that I have asked looking at a company/org is to figure out how to evaluate the whether it’s good or great? And more importantly, how to help drive it to greatness? There’s a list of things that I could rattle off but it was not complete and also, I didn’t really have a structure. That is where the book “Good to Great” by Jim Collins comes into picture. It’s a great book that shares a “framework of ideas” for steering a company from good to great by sharing six key learning’s wrapped in a continual process he calls “flywheel”:

I encourage you to read the book if you can. But if you don’t have time, here’s a good overview:

Like this:

As an analyst or data scientist, its important to have a holistic view of the org that you support. This is important because it will help you in metrics design, project prioritization among other things!

Also, there’s a lot written on what is vision, mission & strategy and the difference between each of these. So this post is not a recap of that but I wanted to share an easy way to remember them:

I am honored to get the PASS outstanding volunteer award again for June 2017! It’s been so much fun helping grow the chapter from 1K to 10K members within last 4 years — the PASS HQ Team & Dan English (Group Lead) were great to work with and there’s so much more growth left for the next few years! The Group was recently classified as a “tier-1” group and got new sponsors which mean that group has some funding to pursue paid growth opportunities that weren’t accessible before.

So since the group has the perfect platform to continue growing and we have a really good process in place to keep our growth flywheel running, I figured it’s a great time to step down. Over the past few years, my career moved me from Business Intelligence -> Analytics -> Data Science and along with that, I have slowly moved away from Microsoft-centric architectures too. I started out working for a Microsoft Gold Partner and then worked for an Open-source heavy shop at a startup-mode organization in silicon valley and now I work in an organization that uses a little bit of everything. Something like best of both worlds — and so there’s a much bigger gap now between where my career is taking me and the mission of the business analytics virtual group. They don’t perfectly align anymore and even though it’s a very rewarding experience, after some reflection, I figured the group deserves a leader whose mission aligns better than mine does.

I am a data-camp subscriber + mentor w/ springboard + completed free-content on data-quest so familiar w/ all three products in some way.

You need two things to have a successful career:

Strong Foundation

Continuous learning

Let’s talk about Continuous Learning first:

In a field that’s as dynamic as data science, you should always be learning! It could be through your projects at your work, side-projects or online resources.

I would categorize both data-camp and data-quest under this and are great platforms for continuous learning. I am a subscriber on DataCamp and it’s a great platform to just dive in, do some hands-on exercises and learn something new. I love it! I have heard equally positive things about DataQuest so if you are already working in the Industry as a Data Scientist and just want to get deeper technically, then go for these platforms!

You need a strong foundation to get hired as Data Scientist. You would do that by typically having a relevant college degree. But:

A lot of people don’t have relevant college degrees OR

They graduated a few years back and are looking to do a career transition now OR

They are not willing to go back to do multi-year college programs focused on data science

If that’s the case then there’s a new approach in the market where you attend these “boot camps” — you still need some foundation skills like for example: math/programming/statistics to be eligible for Data science boot camps and if you have those basic skills then you can go through these boot camps. There’s a bunch of them out there. Just search for “data science boot camps”. Springboard is one of them and I have heard nothing but positive things about them — just like I have about DataCamp & DataQuest. I have personally mentored 6 students so far and all them were looking for a career transition and had nothing but positive things to say! That’s just my empirical data though, you should do a trial w/ them and/or check out their job guarantee through their career track if that is important to you. But either ways, it’s a “Bootcamp” offering so it has regular mentor calls/check-in’s, projects, career-coaches, non-technical material like resume tips to give you a structured approach to everything that you might need to get hired as a data scientist — You can expect intense guided learning over a short period of time. The Bootcamp approach is different than self-learning and self-paced approach by DataCamp & DataQuest.

I am not saying that you can’t break into Data Science with just DataCamp and DataQuest — you would need to complement it w/ other resources and put more effort to cover everything that you may need. With enough motivation, it could be done for sure! Depending on how fast you want to break into data science + how much time you can invest in figuring out the right resources are two of the biggest factor to determine if you need to go through a Bootcamp.

Conclusion:

If you are already working as a data scientist, DataCamp and DataQuest are great for continuous learning! If you are new to this and don’t have a relevant education background then boot camps like Springboard are a great choice.

It’s been close to a year that I have mentored students on the Springboard platform — I found that It’s a great way for students to accelerate their learning through mentorship & structured course material — And so If you considering data analytics or data science courses, I would recommend to check out Springboard as well!

And Here’s the link to get $100 discount code for any Springboard Course:

As a data professional, you would invariably end up spending a lot of time on data cleaning & transformation and a lot of times, you might be doing your work in Excel — if so, then check out Power Query if you haven’t already! It will save you a LOT of time and unlock Jedi powers that you didn’t know you had!

BUT…

if you are using a Mac — and there’s a lot of data scientist and data analyst who are on this platform then you are unfortunately out of luck! So for Mac users out there, I had shared this feedback which has 50 comments & 337 votes (as of 6/16/17) on the official Power BI ideas site; If you are one of the Mac users, then I encourage you to check it out and vote! Microsoft does take it seriously and their roadmap is heavily influenced by ideas site.